Number of found records: 11
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PINTO, María |
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Abstracting/Abstract Adaptation to Digital Environments: research trends. |
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Journal of Documentation, 2003, vol. 59, n. 5, pp.581-608 |
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On line (11/05/2005) |
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The technological revolution is affecting the structure, form and content of documents, reducing the effectiveness of traditional abstracts that, to some extent, are inadequate to the new documentary conditions. Aims to show the directions in which abstracting/abstracts can evolve to achieve the necessary adequacy in the new digital environments. Three researching trends are proposed: theoretical, methodological and pragmatic. Theoretically, there are some needs for expanding the document concept, reengineering abstracting and designing interdisciplinary models. Methodologically, the trend is toward the structuring, automating and qualifying of the abstracts. Pragmatically, abstracts networking, combined with alternative and complementary models, open a new and promising horizon. Automating, structuring and qualifying abstracting/abstract offer some short-term prospects for progress. Concludes that reengineering, networking and visualising would be middle-term fruitful areas of research toward the full adequacy of abstracting in the new electronic age |
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Abstracting; Abstracts; Research; Electronic Document Delivery; Quality Function Deployment |
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SALTON, Gérard; SINGHAL, Amit; MITRA, Mandar; BUCKLEY, Chris |
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Automatic text structuring and summarization. |
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Information Processing and Management, 1997, vol. 33, n.2, pp.193-207. |
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On line (12/05/2005) |
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Contribution to a special issue on methods and tools for the automatic construction of hypertext. Applies the ideas from the automatic link generation research to automatic text summarisation. Using techniques for inter-document link generation, generates intra-document links between passages of a document. Based on the intra-document linkage pattern of a text, characterises the structure of the text. Applies the knowledge of text structure to do automatic text summarisation by passage extraction. Evaluates a set of 50 summaries generated using these techniques by comparing them to paragraph extracts constructed by humans. The automatic summarisation methods perform well, especially in view of the fact that the summaries generated by 2 humans for the same articles are surprisingly dissimilar. (AU) |
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Automatic text analysis; Abstracting |
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Amini, Massih R.; Tombros, Anastasios; Usunier, Nicolas; Lalmas, Mounia |
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Learning-based summarisation of XML documents |
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Information Retrieval, 2007, Vol. 10 Issue 3, pp 233-255 |
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On line (04/2008) (Only UGR) |
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Documents formatted in eXtensible Markup Language (XML) are available in collections of various document types. In this paper, we present an approach for the summarisation of XML documents. The novelty of this approach lies in that it is based on features not only from the content of documents, but also from their logical structure. We follow a machine learning, sentence extraction-based summarisation technique. To find which features are more effective for producing summaries, this approach views sentence extraction as an ordering task. We evaluated our summarisation model using the INEX and SUMMAC datasets. The results demonstrate that the inclusion of features from the logical structure of documents increases the effectiveness of the summariser, and that the learnable system is also effective and well-suited to the task of summarisation in the context of XML documents. Our approach is generic, and is therefore applicable, apart from entire documents, to elements of varying granularity within the XML tree. We view these results as a step towards the intelligent summarisation of XML documents.(AU) |
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Summary; electronic document; xml |
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BUYUKKOKTEN, Orkut; GARCÍA-MOLINA, Héctor; PAEPCKE, Andreas |
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Seeing the Whole in Parts: Text Summarization for Web Browsing on Handheld Devices |
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Digital Library Project (InfoLab), Stanford University, The 10th International WWW Conference Hong Kong, China - May 1-5, 2001 |
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On line ( 15/06/2004) |
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We introduce five methods for summarizing parts of Web pages on handheld devices, such as personal digital assistants (PDAs), or cellular phones. Each Web page is broken into text units that can each be hidden, partially displayed, made fully visible, or summarized. The methods accomplish summarization by different means. One method extracts significant keywords from the text units, another attempts to find each text unit's most significant sentence to act as a summary for the unit. We use information retrieval techniques, which we adapt to the World-Wide Web context. We tested the relative performance of our five methods by asking human subjects to accomplish single-page information search tasks using each method. We found that the combination of keywords and single-sentence summaries provides significant improvements in access times and number of pen actions, as compared to other schemes. (AU) |
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Personal Digital Assistant; PDA; Handheld Computers; Mobile Computing; Summarization; WAP; Wireless Computing; Ubiquitous Computing |
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